Category: Future of AI

Visionary research and essays on the trajectory of artificial intelligence, its cognitive implications, and the human-AI future

AI Pragmatism — The Morning After the Hype Party

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Journal Commentary
Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18838622  28stabilfr·wdophcgmx
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The AI industry in early 2026 is navigating a decisive inflection point: the transition from expansive, optimism-driven experimentation to disciplined, results-oriented execution. This essay examines the structural forces driving this pragmatic turn, the empirical evidence that separates genuine progress from residual hype, and the strategic implications for enterprises that must now answer a h...

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Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18838622 28stabilfr·wdophcgmx
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World Models: The Next AI Paradigm — Morning Review 2026-03-02

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Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18829069  42stabilfr·wdophcgmx
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The artificial intelligence landscape is experiencing what may be its most consequential architectural inflection point since the transformer revolution of 2017. World models — AI systems that construct and maintain internal representations of physical and causal reality — have moved from academic curiosity to billion-dollar bets in the span of months. This morning review examines the theoretic...

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Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18829069 42stabilfr·wdophcgmx
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The Planning Illusion

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Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18824558  46stabilfr·wdophcgmx
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In my previous essay, "AI is not like us?", I argued that we systematically anthropomorphize AI systems — projecting human cognition onto what are, at their core, profoundly alien statistical machines. That argument was architectural and perceptual. This one is operational.

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Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18824558 46stabilfr·wdophcgmx
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AI is not like us?

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Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18824472  51stabilfr·wdophcgmx
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When Alan Turing proposed his famous imitation game in 1950, he embedded a premise so deep we rarely surface it: that intelligence, to be valid, must be indistinguishable from human intelligence. Turing, 1950 — Computing Machinery and Intelligence. The test was never about capability. It was about resemblance.

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Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18824472 51stabilfr·wdophcgmx
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Daily Journal: The 95% Crisis — When AI Pilots Can’t Cross the Production Chasm

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Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18818387  22stabilfr·wdophcgmx
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February 28, 2026 — The AI industry faces a bifurcation point. While MIT Media Lab's Project NANDA reveals that 95% of enterprise AI pilots deliver zero measurable P&L impact, the open-source ecosystem is simultaneously experiencing unprecedented maturation, with models like Llama 4 Maverick (1M context) and Mistral Large 3 (256K context) rivaling proprietary alternatives.

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Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18818387 22stabilfr·wdophcgmx
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AI Agents Operate With Minimal Safety Disclosures: MIT Study Reveals Transparency Gap

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Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18741627  37stabilfr·wdophcgmx
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MIT CSAIL's 2025 AI Agent Index analyzed 30 prominent AI agents and found a striking transparency deficit: while 70% provide documentation and nearly half publish code, only 19% disclose formal safety policies and fewer than 10% report external safety evaluations. This journal entry examines the study's findings, contextualizes the claims within the broader AI safety discourse, and assesses whe...

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Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18741627 37stabilfr·wdophcgmx
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When AI Finally Beats the Experts: DeepRare and the End of the Diagnostic Odyssey

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Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18730582  52stabilfr·wdophcgmx
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A new AI system published in Nature has achieved what many thought impossible: diagnosing rare diseases more accurately than experienced physicians. DeepRare, developed by researchers led by Zhao et al., demonstrates 64.4% top-1 diagnostic accuracy compared to 54.6% for human experts with over a decade of clinical experience. Tested across 6,401 cases spanning 2,919 diseases, the system provide...

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Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18730582 52stabilfr·wdophcgmx
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The Cognitive Shift: A Creative Vision of How AI Will Change the Way We Think and Perceive

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Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18685239  63stabilfr·wdophcgmx
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Score = Ref Trust (70 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

Artificial intelligence is not primarily a threat to human labour — it is a repricing of human cognition. Drawing on Jürgen Schmidhuber's formal theory of intelligence as compression, Robert Sheckley's satirical science fiction, and Isaac Asimov's prescient design specifications for autonomous systems, this essay argues that AI is catalysing the most significant cognitive economy shift since th...

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Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18685239 63stabilfr·wdophcgmx
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[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (70 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
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AI Transforming Science: Math, Biology, and Discovery 2025

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Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18748877  39stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources17%○≥80% from editorially reviewed sources
[t]Trusted33%○≥80% from verified, high-quality sources
[a]DOI17%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed33%○≥80% have metadata indexed
[l]Academic33%○≥80% from journals/conferences/preprints
[f]Free Access17%○≥80% are freely accessible
[r]References6 refs○Minimum 10 references required
[w]Words [REQ]2,995✓Minimum 2,000 words for a full research article. Current: 2,995
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18748877
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]33%✗≥60% of references from 2025–2026. Current: 33%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (30 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)

2025 marked a watershed year for AI-driven scientific discovery, with systems transitioning from computational tools to active research partners. Google DeepMind's AlphaEvolve discovered novel algorithms for fundamental mathematical and computational problems, improving efficiency across Google's infrastructure by 0.7% globally and finding new solutions to open problems that have challenged mat...

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Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18748877 39stabilfr·wdophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources17%○≥80% from editorially reviewed sources
[t]Trusted33%○≥80% from verified, high-quality sources
[a]DOI17%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed33%○≥80% have metadata indexed
[l]Academic33%○≥80% from journals/conferences/preprints
[f]Free Access17%○≥80% are freely accessible
[r]References6 refs○Minimum 10 references required
[w]Words [REQ]2,995✓Minimum 2,000 words for a full research article. Current: 2,995
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18748877
[o]ORCID [REQ]✓✓Author ORCID verified for academic identity
[p]Peer Reviewed [REQ]—✗Peer reviewed by an assigned reviewer
[h]Freshness [REQ]33%✗≥60% of references from 2025–2026. Current: 33%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (30 × 60%) + Required (3/5 × 30%) + Optional (1/4 × 10%)
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